DocumentCode :
2079772
Title :
Image data compression by adaptive vector quantization of classified wavelet coefficients
Author :
Ancis, M. ; Giusto, D.D.
Author_Institution :
Cagliari Univ., Italy
Volume :
1
fYear :
1997
fDate :
20-22 Aug 1997
Firstpage :
330
Abstract :
The paper deals with a novel technique for image data compression based on adaptive vector quantization of wavelet coefficients. High compression factors can be achieved without loosing the informative content of each subband for the statistical properties of these coefficients. Performance of this approach, evaluated on a wide variety of pictures, is far better than the JPEG one, both in quantitative terms (PSNR) and in qualitative ones (absence of blockness distortion)
Keywords :
adaptive codes; image coding; image representation; transform coding; vector quantisation; wavelet transforms; adaptive vector quantization; classified wavelet coefficients; data compression; high compression factors; image coding; image compression; statistical properties; subband coding; wavelet representation; Data compression; Frequency; Image coding; Image resolution; Iterative algorithms; PSNR; Signal resolution; Statistical distributions; Vector quantization; Wavelet coefficients;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Communications, Computers and Signal Processing, 1997. 10 Years PACRIM 1987-1997 - Networking the Pacific Rim. 1997 IEEE Pacific Rim Conference on
Conference_Location :
Victoria, BC
Print_ISBN :
0-7803-3905-3
Type :
conf
DOI :
10.1109/PACRIM.1997.619966
Filename :
619966
Link To Document :
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